数字经济周报（2026年第7期）：GTC2026亮点：AI从芯片竞争迈向系统竞争-20260323

Core Insights - The GTC 2026 conference marks a shift in AI competition from chip-based to system-based, establishing a trend towards platformization of computing infrastructure [2][4] - The AI industry is entering a high-growth expansion phase, driven by increasing demand for computing power and capital investment [2][3] - The digital economy in China is fostering collaborative growth across the industrial chain, with a deepening integration of data elements and industries [2][4] - Global competition in AI is accelerating towards a systematic evolution, with parallel expansion of AI standards and computing infrastructure [2][4] Section Summaries Focus of the Report: GTC 2026 Driving AI Infrastructure Competition Upgrade - The GTC 2026 conference emphasizes the transition from chip upgrades to system upgrades in AI infrastructure, confirming the trend towards platformization [4] - The demand structure for AI is shifting from training-dominated to inference-driven, indicating a change in the nature of AI requirements [4] - The concept of physical AI is gaining traction, with accelerated implementation in real-world systems [4] AI Industry and Representative Company Dynamics - The global AI model token usage has reached a record high of 18.2 trillion calls, indicating explosive growth in demand [17] - The competitive landscape is solidifying around a dual-engine model driven by the US and China, with a significant shift in competitive focus [17] - Major AI companies are experiencing a surge in performance, infrastructure investment, and strategic positioning within the ecosystem [23] China Dynamics: Digital Economy Driving Collaborative Growth - The digital economy is enhancing collaborative growth across various sectors, with a focus on integrating data elements into industrial processes [2][4] Overseas Dynamics: US Launches "AI Export Plan" - The US is initiating an "AI export plan," which is expected to influence global AI standards and infrastructure development [2][4] Technological Frontiers: Breakthroughs in Intelligent Agents and Multimodal Models - Significant advancements are being made in intelligent agents and multimodal foundational models, which are crucial for the future of AI applications [2][4] Think Tank Perspectives: Data Governance in the Era of AI Agents - The increasing penetration of AI applications in educational contexts is prompting a reevaluation of cognitive capabilities and governance models [2][4]